Historically, semiconductor device manufacturers have managed the transition to tighter process/materials specifications by depending on process tool manufacturers to design better and faster process/hardware configurations. As device geometries shrink to the nanometer scale, however, the increasing complexity of manufacturing processes has changed the landscape that must be negotiated to meet and maintain process/materials specifications.
Stand-alone control of process tools (based on equipment state data) will not maintain viable yields at 65 and 45 nm. Advanced device processing requires tool-level control based on the combination of advanced equipment control (AEC) and sensor based process control. Furthermore, tool level control alone cannot meet all of the control needs of advanced device fabrication. System-wide implementation of advanced process control (APC) that integrates AEC with e-diagnostics, Fault Detection and Classification (FDC) and predictive mathematical models of the device manufacturing process are required.
Economic as well as technological drivers exists for the move to AEC/APC. The cost of purchasing (and developing) stand-alone process tools to meet advanced production specifications is expected to be staggering. A cost effective alternative to the purchase of a new generation of process equipment exists through the combined use of add-on sensors with AEC/APC in existing (legacy) equipment. Sensor-based AEC/APC in legacy equipment can drive these tools to the tighter specifications needed for nanometer-scale device fabrication. Additional cost benefits can be realized from reductions in scrap/rework (especially in 300 mm wafer processing) and in lower test wafer use since these can be reduced or even eliminated in systems using wafer- and/or process-state data for process control. Sensor-based AEC/APC can also reduce preventive maintenance downtimes and time to process qualifications, while increasing process capabilities, device performance, yields and fabrication throughput.
A need therefore exists for improved systems and methods for monitoring manufacturing processes. A need also exists for detecting and classifying faults associated with manufacturing processes and outputs of the manufacturing processes.